Endoscopic appearances of gastric mucosa in different endoscopic models according to H. pylori infection status

Abstract Background H. pylori infection has been recognized as a type 1 carcinogen of the gastric malignancy; therefore, early diagnosis and treatment are the corner stone of eradication. Recent findings have also shown that atrophy and intestinal metaplasia remain after successful eradication, which moderately increases the risk of gastric cancer compared with those who have never infected, so the evaluation of gastric mucosa during gastroscopy is important. Aims We aimed to describe and summarize the reliable literature and proposed features of H. pylori infection status and gastritis in research on newly developed endoscopic models that influence clinical practice. In the result, conventional white light endoscopic, image‐enhanced endoscopic models, and studies related to the Kyoto classification of gastritis were searched and reviewed. Results Kyoto classification of gastritis and modified Kyoto classification scoring model for gastritis using conventional white light image (CWLI) endoscopy is an effective tool for evaluating current H. pylori infection status, past infections, eradications, noninfections, and pre‐cancerous conditions. This model is widely used, low cost, and time‐efficient, and is supported by recent findings. Advanced image‐enhanced endoscopic models combined with magnifying endoscopy provide more clear endoscopic features for H. pylori infection status and early gastric cancer. Conclusion According to H pylori infection status, endoscopic prediction of gastric mucosal surface architecture analysis is possible, which influences clinical management. Endoscopic models might lead us to accurate and early diagnose of H. pylori infection status and may not be effective only for the eradication of H. pylori infection but also in the detection of early gastric cancer status.


Introduction
Newly developed models of endoscopic examination can detect the atrophy and intestinal metaplasia of the gastric mucosa that may persist after eradication of H. pylori infection and increase the risk of gastric cancer relative to those never infected.Accordingly, during endoscopy, evaluation of the gastric mucosa for H. pylori infection, along with other diagnostic tests such as urea breathe (UBT), stool antigen test (SAT) and rapid urease test (RUT), is important not only for the diagnosis of H. pylori but also for pre-cancerous gastric lesions.H. pylori infection prevalence is around 50% worldwide and is the leading cause of chronic gastritis, 1 which is classified as class I carcinogen by World Health Organization and International Agency for Research of cancer. 2 Gastric cancer is a fatal disease, with only one in five people surviving for more than 5 years. 1 Most of gastric adenocarcinomas, particularly of intestinal type, is associated with phenotypic changes that result from chronic inflammation induced or initiated by H. pylori infection. 3 addition to earlier whit light image (WLI) endoscopy, several new advanced endoscopic imaging modalities and techniques have been developed for differential diagnosis of gastric lesions.In current clinical practice, magnifying endoscopy (ME) and image-enhanced endoscopy (IEE) are essential and useful tools for detecting and accurately describing lesions with histologic features. 4n conventional white light image endoscopy, present gastric mucosal features are presented superficially and grossly. 5owever, image-enhanced endoscopy (IEE), magnifying endoscopy (ME), narrow-band imaging (NBI), blue laser imaging (BLI), artificial intelligence (AI) and autofluorescence imaging (AFI) visualize mucosal membrane and vascular structures along with the diagnosis of H. pylori status and neoplastic lesions well than conventional white light endoscopy. 6,7he objective of this review is to gather and summarize the gastric mucosal imaging features in both conventional white light image and IEE models to the status of H. pylori infection and identify the relevance in clinical practice.Therefore, conventional white light image, IEE models, and related studies to the Kyoto classification were searched and reviewed.

Endoscopic features of H. pylori infection status in various endoscopic models and clinical applicability of these techniques
Nowadays, different endoscopic models and technique are used and each model can be implemented for the detection of H. pylori infection status (current or positive, eradicated, and never infected forms) by their specific endoscopic features.
Conventional white light image endoscopic model in clinical practice.In 2013, Japan Gastroenterology Endoscopy Society developed a series of 19 conventional white light image endoscopic findings of chronic gastritis in the title of "Kyoto classification of gastritis" for the evaluation of H. pylori infection status and the risk of gastric cancer.In this classification, sticky mucus, diffuse redness, spotty redness, mucosal swelling, enlarged/tortuous fold, nodularity, xanthoma, and hyperplastic polyp predict current H. pylori positive infection; normal mucosal appearance of the antrum, angle and body, presence of regular arrangement of collecting venules (RAC), fundic gland polyp (FGP), red streak, and hematin demonstrate absence or H. pylori noninfected gastric mucosa; regression of spotty redness indicates eradicated status of H. pylori infection (see Fig. 1); mucosal atrophy, intestinal metaplasia, enlarged folds, and nodularity suggest pre-cancerous status of gastric mucosa (see Fig. 2). 5,8These findings are also confirmed by Yoshii et al. 9 First, Kimura-Takemoto classification was introduced in Japan for atrophic gastritis. 10Moreover, gastric mucosal swelling and redness were also proposed for H. pylori-induced inflammation. 11iffuse redness like mucosal swelling is a key finding in the current H. pylori positive infection, which is clearly related to the degree of neutrophils and mononuclear cells infiltration caused by H. pylori infection. 12,13H. pylori-infected inflamed mucosa is characterized by continuous mucosal breakdown and vascular remodeling, 14,15 such as persistent inflammation decrease the density of irregular small vessels and regular arrangement of collecting venules (RAC) may reappear in the atrophic mucosa.However, these findings are not common for previous or past infection.H. pylori induced atrophy refers to the current infection, 16 which gradually disappears after eradication, but usually persists even though its boundaries are unclear. 17herefore, individually atrophy is not a unique feature for current or eradicated H. pylori infection.In some previous studies, raised erosion and multiple white and smooth elevated lesions are predicted for previous infection. 18he Kyoto classification of gastritis and other studies have proposed a characteristic feature for H. pylori non-infected gastric mucosa, ideally observed in the gastric body, especially in the lower part of the lesser curvature, through close endoscopic examination using conventional white light image endoscopy.This was first reported by Yagi et al. in 2005. 19Sensitivity and specificity of the RAC appearance are 100% and 90% respectively.Nevertheless, specific view of RAC can be found for H. pylori non-infected status in gastric antrum with conventional white light image endoscopy, 20 but magnifying endoscopy technique can observe easily. 20oreover, in 2010, H. pylori-infected gastric mucosa evaluated by Sheng-Lei Yan et al. by conventional white light image endoscopic and divided gastric mucosa to the H. pylori infection status into four types (see Table 1), and found that conventional white light image endoscopy could detect H. pylori infection in the gastric mucosa without atrophy. 21ecently, the Kyoto classification of gastritis has been revised by Wang et   2). 22The prevalence of H. pylori infection of modified Kyoto classification gastritis scores in the 0, 1, and ≥2 point groups are 1.5%, 45%, and 82%, respectively.Two newly defined patterns, unclear atrophic boundaries (UABs) and regular arrangement of collecting venule features, have been added to the modified Kyoto classification model of gastritis, to prepare evidence to the clinical accuracy of H. pylori gastritis and strengthen the Kyoto classification of gastritis.They assessed the H. pylori infection in three statuses: current, past or eradicated, and noninfected status.Three findings, unclear atrophic boundary, map-like redness, and reappearance of regular arrangement of collecting venules, predict the past or eradicated infection, if one of these three findings is present, confirms the past or eradicated H. pylori infection; nodularity, diffuse redness, and mucosal swelling suggest the current positive infection and have a high ROC/AUC (0.726); and the presence of regular arrangement of collecting venules is identified as highly specific for the noninfected status. 23lover et al. in 2021 strongly proposed gastric body distal part RAC appearance for the H. pylori noninfected status; diffuse redness and mucosal swelling to the current positive infection; and map-like redness for the eradicated or past H. pylori infection status. 24Hirai et al. in 2023 described that careful observation of mucosal atrophy and swelling in mildly atrophic mucosa, which may conform the diagnosis.Kaplan-Meier analysis also identified a higher gastric cancer detection rate in the current positive and eradicated H. pylori status than noninfected status. 25Consistent with previous studies, regular arrangement of collecting venules for H. pylori noninfected status (OR = 32) and diffuse redness (OR = 26.8)for H. pylori current infection are the prominent endoscopic features, and overall diagnostic accuracy rate in the modified Kyoto classification scoring model is 82.9%. 8Sensitivity, specificity, and odd ratio of White light image endoscopic gastric mucosal patterns to the H. pylori status are summarized in Table 3, and a comparison with other endoscopic models are described in Tables 6-8, and Figure 7.
In the conclusion, newly described endoscopic gastric mucosal patterns with previous endoscopic findings of conventional white light image endoscopy can be implemented in the detection of H. pylori infection status and gastric precancerous lesion as accurate and in real-time practice. 6age-enhanced endoscopic models in clinical practice.Magnifying endoscopy (ME), narrow-band imaging (NBI), linked color imaging (LCI), blue laser imaging (BLI), and autofluorescence imaging (AFI) are known as IEE models that enhance the observation of gastric mucosa and mucosal surface vascular structure and have higher accuracy and detection rate in the H. pylori-infected and pre-cancerous status of the gastric mucosa than conventional white light endoscopic model. 6dvanced endoscopic imaging, especially magnifying model, improves the observation of gastric mucus membrane.Mucosal swelling in H. pylori-associated gastritis caused by neutrophils and mononuclear cells infiltration.Vascular destruction and increasing irregular vessels cause gastric pits enlargement or elongation and inflammation disappear the collecting venules. 38gnifying endoscopy (ME).The magnifying endoscopic model enlarges the imaging area, allowing for a clear observation of the gastric mucosal membrane structures.Most magnifying endoscopes have a resolution of less than 10 μm, and during real-time endoscopy, allow for gastric mucosal observation at 80-120 times magnification.As a result, the membrane's micro-surface structure and the microvascular architecture surrounding the gastric pits can be observed in detail. 15With zoomed or magnifying endoscopic technique, the normal view of the fundal mucosal glands and vascular architectures are obviously visible in the pit patterns, mucosal glands have fixed, rounded, or oval (mouth-like) crypt openings, which   are observe as pin-like dark spots in the central part of mucosal glands, surrounded by subepithelial capillary networks (SECNs) and made a honeycomb-like appearance (Fig. 3). 7Magnifying endoscopy strengths the correlation between H. pyloriassociated gastritis and histological findings, in which a good interobserver agreement has been reported. 15H. pylori infection causes consistent or unchangeable chronic inflammation of gastric mucosa and infiltrated cells, degenerated epithelium, and disrupted microvascular system, causing disappearance obvious features of collecting venules (see Fig. 3). 41gi et al. developed a classification for the assessment of stomach mucosal membrane in magnifying endoscopy.Accordingly, Z0 demonstrates normal mucosal collecting venules and true capillaries, which surround the pit as a network and have 93.8% sensitivity and 96.2% specificity.Other three types, Z1, Z2, and Z3, indicates H. pylori-infected mucosa. 41In this manner, Nakagawa's classification divides the gastric mucosa into three patterns through the RAC morphology: R = regular, I = irregular, and O = obscured patterns.R pattern illustrates H. pylori non-infected status with 63.9% and 100% sensitivity, specificity respectively. 42Kawamura et al. focused on the crypts opening white mucosal membrane and divided on white pit and dens white pit.White and dense white pit predict H. pylori infection that have 81.7% and 78.5% sensitivity and specificity, respectively. 43Anagnostopoulos et al. divided gastric mucosa by magnifying endoscopy on four types in Western population (see Table 4 and Fig. 4) and described that the high-resolution magnifying endoscopy is better and high model for the diagnosis of H. pylori-related gastritis than conventional white light endoscopy. 40gnifying with narrow-band imaging endoscopy (ME-NBI).Observation of gastric pit and vascular patterns in the gastric body with ME-NBI is effective in chronic H. pylori-associated gastritis.These findings include: (1) absence or disorganized collection of venules, (2) indistinct or irregular gastric pits, (3) disappearance of normal SECN (Figs. 5 and 6).
A meta-analysis was conducted on ME-NBI, and demonstrated H. pylori infection sensitivity and specificity of 96% and 91%, respectively. 36Qi et al. identified 100%, 92.7%, 83.8%, and 100%, sensitivity, specificity, PPV, and NPV of ME-NBI, respectively. 35Other studies also found high sensitivity (79%) and specificity (81%) of the ME-NBI for H. pylori infection status to the gastric mucosal appearance. 44,45iromitsu Kanzaki et al. evaluated areae gastricae pattern in the corpus with 0.2% indigo carmine chromoendoscopy for the diagnosis of chronic fundic gastritis (CAFG), the extension of which was evaluated with autoflurescence imaging endoscopy, and micro-mucosal structure was examined with magnifying chromoendoscopy and NBI.They illustrated that most areae gastricae showed a foveola-type micro-mucosal structure (82.7%), while the intervening part of areae gastricae had a groove-type structure (98.0%,P < 0.001).Groove-type mucosa had a higher grade of atrophy (P < 0.001) and intestinal metaplasia (P < 0.001) than with foveola type. 46Yasushi Yamasaki et al. also evaluated areae gastricae pattern in the antrum with 0.2% indigo carmine chromoendoscopy for the diagnosis of chronic fundic gastritis (CAFG), the extension of which was evaluated with autoflurescence imaging endoscopy and micro-mucosal structure was examined with magnifying narrow-band imaging (M-NBI) and classified it into groove and white villiform types.Associations among the extent of CAFG, micro-mucosal pattern, and histology were examined.As the extent of CAFG increased, the proportion of white villiform type mucosa increased, whereas that of groove-type mucosa decreased (P = 0.022).The white villiform type mucosa had significantly higher grades of atrophy (P = 0.002) and intestinal metaplasia (P < 0.001) than groovetype mucosa. 47gnifying endoscopy with blue light imaging (ME-BLI).Due to dark field patterns, blue light imaging technology is limited.However, blue light imaging presents clear mucosal and vascular structure appearance with high contrast laser light system.ME-NBI and ME-BLI are effective models for differentiation of H. pylori gastritis and have high sensitivity of 98% and specificity of 92% (see Fig. 7). 29 1b. 39(c): In normal antral mucosa, the SECN is coilÀshaped and no collecting venules can be seen. 40inked color imaging (LCI).The contrast of LCI is twice higher than white light imaging.Moreover, recent studies have been reported three time higher detection rate than conventional white light imaging in the differentiating of abnormal lesions (see Figs. 8 and 9). 6A study in Japan identified positive H. pylori gastric mucosa by LCI more accurately with 93.8% sensitivity and 78.3% specificity than white light imaging. 11,48tificial intelligence (AI).A large prospective randomized controlled study in Japan compared AI and expert endoscopists for the accuracy of diagnosis of H. pylori infection.A total of 32 208 endoscopic images from eight sections of the stomach were classified for H. pylori positive and negative status.
In the result, they identified that AI has higher sensitivity and specificity than endoscopists (81.9%, 83.4% vs. 79% 83.2%). 49nother experimental study in Japan compared Blue Light Image-Bright (BL-bright), Linked Color Imaging (LCI), and conventional white light image (CWLI) with artificial intelligence (AI), the AUC of AI-BLI-bright and AI-LCI were 0.96 and 0.95, respectively, and the AUC of CWLI was 0.66. 49AI is considered a strong focusing method on the global health development system; therefore, studies of Artificial Intelligence endoscopic models are increasing and trying to be applied together with IEE models to improve the endoscopic diagnosis of H. pylori infection status. 50The advantages of AI are providing a second opinion, finding some important features during endoscopy, reducing time consumption, and requiring less training and experience.In the future, AI may become the best diagnostic method for detection of H. pylori infection status.
Autofluorescence imaging (AFI).Videoendoscopy of autofluorescence image (AFI) is a technique of natural tissue autofluorescence that is emitted by light excitation from endogenous fluorophores such as collagen, nicotinamide, adenine dinucleotide, flavin and porphyrins, and in the result produce real-time pseudocolor images. 51Mucosal features, which are not visible with conventional white light endoscopy, AFI can enable detection of these mucosal patterns and might improve the identification and characterization of the gastritis and premalignant status in gastric mucosa. 52Bright green images of gastric mucosa using AFI indicate more inflammation, atrophy, or intestinal metaplasia induced by H. pylori infection.The accuracy for detecting atrophy and intestinal metaplasia was 88% and 81%, respectively, while per-biopsy analysis, the accuracy was 76% for both.However, purple or deep green mucosal images indicate normal fundic mucosa (see Figs. 10 and 11). 52,54Takuya Inoue et al. performed a study in 209 on the diagnosis of chronic atrophic fundal gastritis with AFI and illustrated the accuracy of green mucosa in patients with activity, inflammation, atrophy, and intestinal metaplasia of 64%, 93%, 88% and 81%, respectively; in per-biopsy analysis, the accuracy for activity, inflammation, atrophy, and intestinal metaplasia was 55%, 62%, 76%, and 76%, respectively.Therefore, AFI may be a useful adjunct to endoscopy to identify patients at high risk of developing gastric cancer. 52Another study in Japan was conducted, which received eradication therapy for H. pylori infection and the extent of chronic atrophic fundic gastritis was evaluated by AFI.They revealed that metachronous early gastric cancer developed after successful H. pylori eradication, and extensive atrophic fundic gastritis, which diagnosed by AFI is a significant predictor. 53 EndoFaster (new innovative tool).This is a real-time analytic machine using gastric juice and provide information on gastric pH and ammonium concentration, which was first introduced in 2005.This machine detects the urease enzyme through a urease test in gastric juice, which is produced by H. pylori infection.A volume of 2-4 mL of gastric juice aspirate during OGD and analyzed using the EndoFaster within 1 min. 55,56A large prospective study compared the EndoFaster and urea breath test (UBT) with histological examination as the gold standard for diagnosis of H. pylori infection identified 90.3% and85.5% sensitivity and specificity, respectively.Many other studies also reported high accuracy for the real-time H. pylori infection diagnosis, and it is comparable with the urea breath test (UBT).The overall benefits of EndoFaster are being less invasive, not requiring proton pump inhibitor (PPI), discontinuation before testing, and less costs.Moreover, recent studies have demonstrated that EndoFaster is an useful tool for the detection of hypochlorhydric and neoplastic risk conditions, and as an adjunct to gastroesophageal reflux (GERD) treatment. 57  Diagnostic performance of H. pylori infection in various endoscopic models and clinical applicability.Each endoscopic model and technique could be used for demonstrating H. pylori infection status using the specific endoscopic features.Currently, the focus is on Helicobacter pylori infection, specifically on patients who are H. pylori-positive,

Conclusion
Recent studies demonstrate that various endoscopic imaging models of the gastric mucosa improve the evaluation and  detection of H. pylori status and pre-cancerous lesion by the development of new equipment and models and can present valuable information for clinical and histopathological correlations.Conventional white-light imaging endoscopy with a modified scoring system of the Kyoto classification of gastritis due to its availability, widespread use, less time-consuming, low cost, and no need for more experience is an effective model for the evaluation of H. pylori infection status and pre-cancerous lesion of gastric mucosa.Newly developed image-enhanced endoscopic (IEE) models alone or in combination with magnifying endoscopy are more effective models for the detection of gastric mucosal changes and obtaining accurate targeted biopsies than conventional white light imaging (CWLI) endoscopy.However, using IEE modules requires adequate training and skills along with sufficient experience, time, and specialized advanced equipment to perform the procedures.Therefore, its widespread use is limited and more studies have not been conducted.The use of AI is limited, and there are no further research studies, but it will be a good diagnostic model for the evaluation of H. pylori infection status in the future because of the detection some important features during endoscopy, performed in a short time and require less training.

Figure 3
Figure 3 Gastric body mucosal patterns on magnifying endoscopy.(a): Normal mucosa comprises a honeycomb-type subepithelial capillary network (SECN) with a regular arrangement of collecting venules (arrow) and regular, round pits; (b): Helicobacter pylori (H.pylori)-associated gastritis appears loss of the normal SECN and collecting venules, with enlarged white pits surrounded by erythema; (c): Corresponding histologic features of Figure 1a; (d): Corresponding histologic features of Figure1b.39(c): In normal antral mucosa, the SECN is coilÀshaped and no collecting venules can be seen.40

Figure 4
Figure 4 The gastric body mucosal patterns identified on magnifying endoscopy.(a): The type 1 pattern comprises a honeycomb-type subepithelial capillary network (SECN) with a regular arrangement of collecting venules and regular, (b): The type 2 pattern comprises a honeycombÀtype SECN with regular, round pits, but with loss of collecting venules, (c): In the type 3 pattern, there is loss of the normal SECN and collecting venules, with enlarged white pits surrounded by erythema.(d):The type 4 pattern is characterized by loss of the normal SECN and round pits, with irregular arrangement of the collecting venules.40

Figure 5 6 Figure 6
Figure5(a) H. pylori-negative gastric mucosa is characterized by homogeneous, round pits with regular honeycomb-like SECNs in NBI; (b) H. pylori-positive gastric mucosa is characterized by enlarged or elongated, varies in sized and shaped of pits with unclear SECNs in NBI.6

Figure 7
Figure7(a) H. pylori-negative gastric mucosa is characterized by homogeneous, round pits with regular honeycomb-like SECNs in NBI; (b) H. pylori-positive gastric mucosa is characterized by enlarged or elongated, varies in sized and shaped of pits with unclear SECNs in NBI.6

Figure 9
Figure 9 (a) Diffuse redness in gastric body in WLI; (b) Diffuse redness in gastric body (Deep Reddish Color) in LCI; (c) Diffuse redness in gastric antrum in WLI; (d) Diffuse redness in gastric antrum (Deep Red Color) in LCI.6

Figure 10
Figure10Representative case of closed-type atrophic fundic gastritis in autofluorescence imaging (AFI) images.Cardia is surrounded by purple mucosa, and a color border between green and purple is observed at a lesser curvature of gastric body.53

Figure 11
Figure 11 Representative case of open type atrophic fundic gastritis in autofluorescence imaging (AFI) images.The entire gastric mucosa including cardia looks bright green.53

Table 1 H
21pylori-infected gastric mucosal types in conventional whit light image endoscopic model21

Table 2
Modified Kyoto classification scoring model of gastritis

Table 3
Summary of Sensitivity, specificity, and odd ratio of white light image endoscopic gastric mucosal findings to the H. pylori infection status

Table 4
Types of gastric mucosa in Western population in the magnifying endoscopy

Table 8 .
58e development of endoscopic techniques can reflect histologic patterns of endoscopic images during endoscopy for the real-time diagnosis of H. pylori infection.58

Table 8
Sensitivity, specificity, PPV, NPV, and total diagnostic accuracy of Helicobacter infection in various endoscopic models in recent studies 6acking external validation performance and beingconducted only in Asia should be overcome BLI, blue light imaging; CI, confidence interval; LCI, linked color imaging; NBI, narrow-band imaging; M-BLE,6magnifying with blue light imaging; M-LCI, Magnifying with Linked color imaging; M-NBI, Magnifying with narrow-band imaging; NPV, negative predictive value; PPV, positive predictive value; WLI, white light imaging.